Staring at the Abyss : A Neurocognitive Founded Agent Based Model of Collective-Risk Social Dilemma under the Threat of Environmental Disaster

We propose an agent-based model that explores the dynamics of a collective-social risk dilemma, within the framework of a simplified shallow lake model (Scheffer 1998). The agents are endowed with realistic cognitive abilities, building on the Agent Zero framework (Epstein, 2014). Deliberative, affective and social components are behind the agent decisions, accounting for both bounded rationality and the plurality of channels by which dispositions to act and opinions are transmitted. Individual decisions, aggregated over the entire population, may push a shallow lake over a regime shift threshold where a polluted (turbid) state settles in. This multifaceted model allows us to obtain a more precise understanding of the emergent process of cooperation induced by environmental awareness, and in so doing, it helps us understand how to possibly prevent the transition to the polluted state. To that purpose, we consider various cases on the combination of cognitive modules, and different multilayered network topologies in the population of agents. Simulation results, analyzed with novel computational methods, emphasize that environmental awareness is maximized when the socio-environmental system converges to self-organized criticality. Improved natural conditions, such as higher natural pollution decay, does not result in higher awareness as the agents internalize these constraints and are encouraged to pollute more. These results provide an insightful explanation behind the experimental result that more resistant environments (lower probability of collapse) may shelter a less environmentally concerned population, and that cooperation in the context of collective-social risk dilemma is the strongest when the system is at the edge of collapse